Research Interests

I am interested in a wide variety of disciplines within Statistics. These include, but are not limited to, maximum likelihood estimation, exponential family theory, generalized linear models, envelope methodology, conformal prediction, causal inference, bootstrap techniques, and multivariate statistics. I am generally interested in the tradeoffs between robustness and efficiency in estimation. My CV is attached here.

My research mission is to improve statistical methodologies that are applicable to real-world problems. My focus is placed on both the theoretical and computational aspects of this methodology. To better understand relevant real-world problems, I work closely with scientists and researchers across a variety of disciplines. Writing technical research papers, or an accompanying technical report, that can be understood by the intended scientific audience is central to my research mission. Current methodological work of mine has applications in evolutionary biology, engineering, epidemiology, chemometrics, several domains of physics, and sports.


    Daniel J. Eck, R. Dennis Cook, Christopher Nachtsheim, and Thomas A. Albrecht (2020). Multivariate Design of Experiments for Engineering Dimensional Analysis. Technometrics, 62, 1, 6-20.

    Daniel J. Eck (2020). Challenging nostalgia and performance metrics in baseball. Chance, 33, 1, 16-25. Reproducible technical report here. Shiny app here. FanGraphs article here.

    Si Cheng, Daniel J. Eck, and Forrest W. Crawford (2020). Estimating the size of a hidden finite set: large-sample behavior of estimators. Statistics Surveys, 14, 1-31.

    Daniel J. Eck, Charles J. Geyer, and R. Dennis Cook (2020). Combining Envelope Methodology and Aster Models for Variance Reduction in Life History Analyses. Journal of Statistical Planning and Inference, 205, 283-292. Reproducible technical report here.

    Daniel J. Eck (2018). Bootstrapping for multivariate linear regression models. Statistics and Probability Letters, 134, 141-149.

    Rickard J. Kohler, Susan A. Arnold, Daniel J. Eck, Chris Thomson, Matthew A. Hunt, and G. Elizabeth Pluhar (2018). Incidence of and risk factors for major complications or death in dogs undergoing cytoreductive surgery for treatment of suspected primary intracranial masses. Journal of the American Veterinary Medical Association, 253, 12, 1594-1603.

    Daniel J. Eck and R. Dennis Cook (2017). Weighted envelope estimation to handle variability in model selection. Biometrika, 104, 3, 743-749. Software that implements the methods in this paper was created by Minji Lee and Zhihua Su, see: Renvlp.

    Daniel J. Eck and Ian W. McKeague (2016). Central Limit Theorems under additive deformations. Statistics and Probability Letters, 118, 156-162.

    Daniel J. Eck, Ruth G. Shaw, Charles J. Geyer, and Joel G. Kingsolver (2015). An Integrated Analysis of Phenotypic Selection on Insect Body Size and Development Time. Evolution, 69, 2525-2532. Reproducible technical report here.

In Progress

    Daniel J. Eck and Forrest W. Crawford (2020+). Conformal prediction for exponential families and generalized linear models. Reproducible technical report here.

    Ellen S. Fireman, Zachary S. Donnini, Daniel J. Eck, Yuk-Tung Liu, and Michael Weissman (2020+). Do In-Person Lectures Help? A Study of a Large Statistics Class.

    Olga Morozova, Daniel J. Eck, and Forrest W. Crawford (2020+). Regression and stratification for contagious outcomes.

    Georgiana May, Daniel J. Eck, and Charles J. Geyer (2020+). Do defensive symbionts cause selection for greater pathogen virulence?


    Daniel J. Eck (2018). conformal.glm: Conformal Prediction for Generalized Linear Regression Models.

    Charles J. Geyer and Daniel J. Eck (2016). glmdr: Exponential Family Generalized Linear Models Done Right.

    Daniel J. Eck (2016). envlpaster: Enveloping the Aster Model.